Data warehousing systems are well known in this field of technology. FIG. 1, for example, describes a typical data warehousing methodology known as ETL, which acronym stands for Extract, Transform and Load. In a typical ETL process 10, source data 12 is first extracted 14 by an extraction process. Following the data extraction process 14, the source data is then transformed from its native format as defined by a source data structure into a common format as defined by the data warehouse 20. Although only one data source 12 is shown in FIG. 1, in a typical implementation many data sources, each with distinct native formats, are extracted and transformed into the common format of the data warehouse 20. In this way, disparate data sources and structures can be maintained using the common format of the data warehouse. In these typical multi-source implementations, each distinct native format will require a separate transformation process 16 in order to map the source data into the common format maintained at the data warehouse 20. After the data has been transformed 16, it is then loaded 18 into the data warehouse 20 for long term storage and/or for other data processing operations.